Impact Analysis¶

After running a simulation, CalcBridge provides comprehensive impact analysis showing exactly how your proposed trades would affect every compliance test. This guide explains how to interpret and act on these results.

Understanding the Results¶

Impact Summary¶

Every simulation returns a high-level summary:

{
  "impact_summary": {
    "improve": 5,
    "worsen": 2,
    "neutral": 8
  },
  "new_failures": 0,
  "total_tests": 15
}

Before/After Comparison¶

Each compliance test shows current and projected values:

Test Result Structure¶

Example Result¶

{
  "test_name": "CCC Bucket",
  "test_category": "rating",
  "current_value": 6.50,
  "projected_value": 4.20,
  "threshold_value": 7.50,
  "cushion_current": 1.00,
  "cushion_projected": 3.30,
  "status_current": "pass",
  "status_projected": "pass",
  "impact_direction": "improve"
}

Interpretation: Selling CCC credits reduced CCC exposure from 6.50% to 4.20%, increasing cushion from 1.00% to 3.30%. The test improves significantly.

Impact Direction Logic¶

CalcBridge determines impact direction by comparing cushions:

flowchart TD
    A[Calculate Cushion Change] --> B{Change > 0.01%?}
    B -->|Yes| C{Direction?}
    B -->|No| D[Neutral]

    C -->|Positive| E[Improve]
    C -->|Negative| F[Worsen]

    E --> G[Cushion Increased]
    F --> H[Cushion Decreased]
    D --> I[Minimal Change]

Cushion Calculation¶

For tests where higher is worse (concentration, CCC bucket):

cushion = threshold - current_value

For tests where lower is worse (OC ratio, diversity score):

cushion = current_value - threshold

Impact Thresholds¶

Compliance Test Categories¶

Concentration Tests¶

Monitor exposure limits to single obligors and industries.

Rating Tests¶

Track credit quality exposure.

Coverage Tests¶

Ensure sufficient collateralization.

Quality Tests¶

Monitor portfolio-level metrics.

Diversity Tests¶

Measure portfolio diversification.

Status Transitions¶

Status Values¶

Critical Status Changes¶

Visualizing Results¶

Impact Chart¶

The Impact Chart groups results by category and shows:

• Impact indicator: Arrow up (improve), down (worsen), or right (neutral)
• Current vs Projected values: Side-by-side comparison
• Cushion changes: How much headroom changed
• Status badges: Pass/warning/fail for both states

Compliance Gauge¶

For individual tests, the Compliance Gauge shows:

• Visual arc: Red/yellow/green zones
• Current needle: Where you are today (dashed)
• Projected needle: Where you would be after trades (solid)
• Cushion to breach: Exact headroom remaining

Retrieving Results via API¶

Get All Results¶

curl -X GET https://api.calcbridge.io/api/v1/scenarios/{scenario_id}/results \
  -H "Authorization: Bearer $TOKEN"

Filter by Category¶

curl -X GET "https://api.calcbridge.io/api/v1/scenarios/{scenario_id}/results?category=rating" \
  -H "Authorization: Bearer $TOKEN"

Available categories:

• concentration
• rating
• coverage
• quality
• diversity

Identifying Problematic Trades¶

Finding the Cause of Worsening Tests¶

When a test worsens, analyze which trades caused it:

1. Single Obligor Limit worsening: You may be buying more from an obligor that is already at high concentration
2. CCC Bucket worsening: You may be buying CCC-rated credits or not selling enough
3. Industry Concentration worsening: You may be adding to an already concentrated industry
4. WAS worsening: You may be buying lower-spread credits

Mitigation Strategies¶

Making the Go/No-Go Decision¶

Decision Framework¶

flowchart TD
    A[Review Simulation Results] --> B{New Failures?}
    B -->|Yes| C[Do NOT Proceed]
    B -->|No| D{Worsening Tests?}

    D -->|No| E[Safe to Proceed]
    D -->|Yes| F{Acceptable Risk?}

    F -->|No| G[Modify Trades]
    F -->|Yes| H{Approval Required?}

    H -->|No| I[Proceed with Caution]
    H -->|Yes| J[Seek Approval]

    G --> A
    C --> G
    J --> K{Approved?}
    K -->|Yes| I
    K -->|No| G

Approval Checklist¶

Before executing trades that worsen any test:

• No new failures would be caused
• Remaining cushion is sufficient for normal volatility
• Trade rationale justifies the compliance impact
• Approval obtained from appropriate authority
• Documentation of decision rationale

Exporting Results¶

For Documentation¶

Export simulation results for compliance records:

import json

# Fetch results
results = get_simulation_results(scenario_id)

# Format for documentation
report = {
    "scenario_name": results["scenario_id"],
    "simulation_date": "2026-01-25",
    "summary": results["impact_summary"],
    "new_failures": results["new_failures"],
    "tests": results["results"]
}

# Save to file
with open("simulation_report.json", "w") as f:
    json.dump(report, f, indent=2)

For Approval Workflow¶

Include in approval request:

1. Scenario name and purpose
2. List of proposed trades
3. Impact summary (improving/worsening/neutral counts)
4. Any new failures or warnings
5. Tests with reduced cushion
6. Recommendation

Audit Trail¶

All simulations are logged for compliance auditing:

Access audit logs via the admin API or export for external audit systems.

Next Steps¶

After analyzing your results:

• Learn best practices for scenario workflows
• Review the API reference
• Understand compliance testing